1a. Objectives (from AD-416):
1. Improve methods for the quantification of emissions from individual agricultural sources and whole agricultural facilities or management operations.
2. Develop methods to predict emissions and their dispersion from individual sources and whole facilities or management operations.
3. Validate the prediction tools for a variety of agricultural sources.

1b. Approach (from AD-416):
In a previous project a prototype lidar system for measuring particulate matter emissions was developed and evaluated. This system will be refined to improve the portability, usability and reliability for routine measurements across a wide variety of agricultural systems. Evaluation of the system will include comparisons against in situ samples of particulates to increase the reliability of the method using accepted EPA verification methodologies. Comparisons will be used to provide detailed specifications of the performance capabilities of the unit. Evaluation of the emissions measurement capabilities will be conducted under laboratory and field conditions. Integration of the particulate and gaseous units with ancillary micrometeorology will be coordinated with ARS scientists during field measurements. The development of new systems for the measurement of gaseous emissions from agricultural sources will include identification of the most critical gases of interest to agriculture, characterization of system capabilities, and performance compared to accepted standards. A project review will be conducted during the first year.

3. Progress Report:
Airborne particles, especially particulate matter (PM) 10 micrometers (µm) or smaller in aerodynamic diameter (PM10) and fine particulate matter 2.5 µm or smaller in aerodynamic diameter (PM2.5), are microscopic solids or liquid droplets in the air that can cause serious health problems (e.g., coughing, difficulty breathing, decreased lung function, asthma, heart attacks, and premature death), especially in people with heart and lung disease. Concern with health effects resulting from PM10 exposure is drawing increased regulatory scrutiny and research toward local agricultural tillage operations. To investigate the control effectiveness of one of the current Conservation Management Practices (CMPs) a study was designed to: 1) evaluate the magnitude, flux, and transport of PM emissions produced by agricultural practices for row crops where tillage CMPs are implemented vs. the magnitude, flux, and transport of PM emissions produced by agricultural practices where CMPs are not implemented; 2) determine the control efficiencies of equipment used to implement the “conservation tillage” CMP; and 3) assess whether CMPs for a specific crop can be quantitatively compared, controlling for soil type, soil moisture, and meteorological conditions. This study used advanced measurement technologies, which link lidar systems with conventional point-measurement air quality samplers, to map PM emissions at high spatial and temporal resolution in order to accurately compare CMPs with conventional tillage systems. The purpose of this field study was to determine if and how much particulate emissions differ between the conventional method of agricultural fall tillage and a conservation tillage CMP. An extensive network of measurement systems were used during this study, including a scanning lidar, a full meteorology suite, four sonic anemometers (for turbulence information), and filter and optical aerosol point samplers. Two additional aerosol chemical analysis systems were employed from a sampling trailer located on the downwind side of the field under test. Tillage particulate emission rates were determined using two methods: 1) inverse modeling coupled with observed facility-derived concentrations from filter- and optical-based instruments; and 2) a mass balance approach applied to upwind and downwind PM concentrations measured by the lidar. The tillage emissions were modeled using two different air dispersion models: the Industrial Source Complex Short-Term Model, version 3 (ISCST3) and the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD). Emission data calculated for each measurement method for the conventional and conservation tillage operations are presented herein. The study showed that the conservation practice required <1/4 of the number of tractor passes when compared to conventional tillage; similar reductions in fuel use and tractor exhaust associated PM10 emissions were expected to have occurred. Lidar-derived and inverse modeling emission rates for PM2.5, PM10, and total suspended particulate (TSP) by operation, as well as the average tillage rate in hours per hectare are summarized herein. Based on lidar data, the conservation tillage method reduced PM2.5 emission by 91%, PM10 by 94%, and TSP by 91%, which were all statistically significant differences. Reduced emissions, as calculated using inverse modeling and optical particle counter data, are very close to lidar-derived reductions at 85%, 87%, and 90% for PM2.5, PM10, and TSP, respectively. The time per hectare required to perform the conservation tillage was about 14% of the conventional method. The control efficiency of the Conservation Management Practice for particulate emissions was 0.905, 0.937, and 0.909 for PM2.5, PM10, and TSP, respectively, based on lidar data and 0.853, 0.872, and 0.903 for PM2.5, PM10, and TSP, respectively, based on inverse modeling with optical particle counter data.